globalchange  > 气候变化与战略
DOI: 10.1007/s11069-020-04029-1
论文题名:
What matters the most? Understanding individual tornado preparedness using machine learning
作者: Choi J.; Robinson S.; Maulik R.; Wehde W.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期:1
起始页码: 1183
结束页码: 1200
语种: 英语
中文关键词: Disaster management ; Emergency preparedness ; Machine learning ; Random forest regression ; Tornado preparedness
英文关键词: computer simulation ; decision making ; disaster management ; disaster relief ; machine learning ; tornado
英文摘要: Scholars from various disciplines have long attempted to identify the variables most closely associated with individual preparedness. Therefore, we now have much more knowledge regarding these factors and their association with individual preparedness behaviors. However, it has not been sufficiently discussed how decisive many of these factors are in encouraging preparedness. In this article, we seek to examine what factors, among the many examined in previous studies, are most central to engendering emergency preparedness in individuals particularly for tornadoes by utilizing a relatively uncommon machine learning technique in disaster management literature. Using unique survey data, we find that in the case of tornado preparedness the most decisive variables are related to personal experiences and economic circumstances rather than basic demographics. Our findings contribute to scholarly endeavors to understand and promote individual tornado preparedness behaviors by highlighting the variables most likely to shape tornado preparedness at an individual level. © 2020, Springer Nature B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168431
Appears in Collections:气候变化与战略

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作者单位: The University of Oklahoma, 455 West Lindsey, 205 DAHT, Norman, OK 73019, United States; Henry Bellmon Chair of Public Service, The University of Oklahoma, 455 West Lindsey, 304E DAHT, Norman, OK 73019, United States; Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, IL 60439, United States; East Tennessee State University, 301C Rogers-Stout Hall, P.O. Box 70651, Johnson City, TN 37614, United States

Recommended Citation:
Choi J.,Robinson S.,Maulik R.,et al. What matters the most? Understanding individual tornado preparedness using machine learning[J]. Natural Hazards,2020-01-01,103(1)
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